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Oral

2025 Symposium on Hydro-climate and Climate Change (Watershed)

Seasonal Inflow Forecasting Based on a Physically Based Hydro-Climatic Model for the Shasta Lake Basin, California

Monday, May 19, 2025
4:45 PM – 5:00 PM Alaska Daylight Time (AKDT)
Room: Room 1
Abstract Submission: Seasonal forecasting is essential for effective water resource management, but it remains challenging, especially in the context of climate change and the added uncertainty it brings. It is becoming increasingly clear that purely statistical inflow forecasting is insufficient. This study applies the seasonal snow and inflow forecasting system, developed by the Hydrologic Research Laboratory at the University of California, Davis, for seasonal forecasting in the Shasta Lake Basin, California. The system is based on the WEHY Hydroclimatic Modeling System, a physically-based modeling framework.
The system operates in three primary stages. First, the WRF model is used to downscale forecasts from the CFSv2 data to a 9 km resolution. These forecasts are then integrated into the WEHY model to produce a 15-member ensemble of snow and inflow forecasts. Finally, the inflow forecasts are updated using a statistical updating system, which uses an exponential smoothing model. An ensemble of forecasts is produced monthly from January to June, providing forecasts from the month following the initialization through to July. The inflow forecasts revealed that the deterministic predictions tended to overestimate inflows during dry years, primarily due to overpredicted precipitation forecasts. However, the statistical updating of these deterministic forecasts using the seasonal exponential smoothing model significantly improved accuracy, with monthly flows aligning closely with observed full natural flows. This system demonstrates strong potential for seasonal inflow forecasting and could greatly enhance informed water resource management in the Shasta Lake Basin.

Learning Objectives/Expected Outcome (Optional) :